核函数

Nonparametric estimation of average treatment effects under exogeneity:a review ［J］.

周志丹。回归函数的核估计法及其在经济分析中的应用［J］。

For a well-posed initial value problem of PDE, this paper estimates the values of its unknown functions on the initial surface with the kernel method in nonparametric regression analysis to deal with the data collected at different time and different positions.

对于一个适定的偏微分方程组广义初值问题，该文利用非参数回归分析中的核估计方法，对在不同时间和不同空间记录下的数据进行整合，估计出未知函数在初始曲面上的值。

The semi-low normal distribution membership function of fatigue limit is determined, and the anti-fatigue fuzzy reliability compute formula of rotor is deduced. The fuzzy reliability model of rotor anti-fatigue is set up. Taking an internal shaft of the rotor of aero electric generator for an example, its reliability design can be realized by adopting the anti-fatigue reliability design theory presented in the dissertation.

首次确定出了疲劳极限降半正态分布形式的隶属函数，推导出了转轴抗疲劳的模糊可靠度计算公式，建立了转轴抗疲劳的模糊可靠性模型；以航空发电机转子内轴为例，对其进行了抗疲劳的可靠性设计，并用本文建立的抗疲劳的模糊可靠度计算公式，对其进行了模糊可靠性校核。

EMC effects reflect that free nucleon structure functions are different from bound nucleon.

EMC效应的发现反映了自由核子与束缚核子的结构函数明显不同，核环境可以影响核子的内部结构。

Based on the analysis of the basic theory of in the new method for processing the no-line date-The Kernel Methods, the basic principles of the multiclass classifying based on the One-class Classification have been studied.

在分析非线性数据处理新方法一核方法理论的基础，研究基于一类分类方法的多类分类的基本原理，提出应用于多类分类的可信度函数，使分类的结果更具有可信度。

The ICA is a kind of signal processing method based on high order statistic, it can recover the source signals from the linearly mixed signals, but it has disadvantages in processing non-linearity signals, and the KICA, which is based on nonlinear function space, can solve the problem effectively. Comparing with current ICA algorithms, the KICA is notable for its flexibility and robustness.

独立分量分析是近几年发展起来的基于信号高阶统计特性的分析方法，它是指从多个源信号的线性混合信号中分离出源信号的技术，但目前的算法在处理非线性变化的信号时还有一定的局限，而基于非线性函数空间的ICA方法－KICA，即核独立成分分析，可以解决这一问题。

As to nonparametric and semiparametric regression models, the most widely used regression methods include: local smoothness, including Nadaraya-Watson kernel estimate, Gasser-Muller estimate, local polynomial method; spline method(such as smoothing spline, spline penalies and so on); other is orthogonal series estimates, such as Fourier series and so on.

本文主要介绍Nadaraya-Watson核估计方法对非参数模型估计的思路和估计方法，变系数模型中函数系数的局部多项式估计，包括估计思路，估计计算。

Then, the prior probability of the background and foreground is estimated with Baysian theory.

该算法利用贝叶斯模型结合核密度函数理论，把阈值的选取放到概率空间上考虑，给出了在复杂的动态背景下检测出运动目标的方法。

In the second part , also under NA assumption, we worked on the consistency of kernel estimator of regression function in the nonparametric regression model Y_i =g+ε_i.

第二部分：我们研究了样本为NA相依的情况下，非参数回归模型Y_i=g+ε_ii=1，2，…，n中，回归函数核估计的强，弱相合性。

This dissertation highlights neural network models and learning algorithms related, which are playing an equally important role in neural network research. The main results obtained are presented as follows: Reproducing kernel developed in different disciplines has become an importanttool in functional approximation.

神经网络模型和与之相适应的训练算法是本文研究的重点，它们在神经网络的研究中占有同样重要的位置，本文获得的主要结果如下：再生核源于不同学科分支，目前已成为函数逼近的重要工具。

But we don't care about Battlegrounds.

但我们并不在乎沙场中的显露。

Ah! don't mention it, the butcher's shop is a horror.

啊！不用提了。提到肉，真是糟透了。